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4,145 ideas

Atlasphere – Live Infrastructure Diagrams

Hi HN. My name is Andrey. On a regular business day, I'm a software engineer working at AWS. Outside of work hours, I spend time on my hobby - writing code.I was once building a pet project that allowed customers to spin up fully synchronized blockchain nodes within just a few minutes. The backend was split into a control plane and a data plane, each with its own AWS account. Later I added two more AWS accounts. One for shared RPC nodes. One for the Analytics Service.Since I love to visualize things, I used drawio to visualize the architecture.With time, I noticed a pattern. I'd write some code, add a few lambda functions, update my drawio diagram, write more code, introduce a few more resources, test things, see that everything works fine and go to sleep with a smile on my face. Next week I'd check my diagram, and shockingly, it's missing some of the resources! This kept happening for a few more weeks until I decided to fully abandon the project until my infrastructure diagrams could stay in sync with my cloud account.That's how Atlasphere.io was born. I've been working on it for the past 6 months and I think the product is ready for some feedback :)A few notes:- Atlasphere uses a ReadOnly IAM role to scan your AWS account (my account reaches your account through a trust relationship).- The number of services is currently limited (WIP)- It's a macOS app- It's NOT an Electron app, i use Rust + WebviewWhat am I looking for? All I really need is for someone to try the app and tell me what they like about it and what they absolutely hate about it, haha!The website is https://atlasphere.io/

Hacker News3mo agoToolAI

62FL score
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Learn from 30 historical figures, open source, nonprofit, self-hosted

Hello HN, I am the founder of Agora Cosmica.This started about three years ago. On a walk I asked a chatbot to interpret the cave dream from Cormac McCarthy's book "The Road" as C.G. Jung. It gave me a perspective I had not thought of. But for my own dreams the policies of the big providers felt wrong for so personal conversations, as zero data retention is not available. So I started building.The project evolved to a German nonprofit and we published the code (AGPL-3.0) last month. The content is still copyright, but will be opened to CC-BY 4.0 in the next 6 to 12 months.Agora Cosmica is a library to learn from 30 historical figures. Each one has 12 narrated stories about their teachings / life wisdom, speech to speech conversation. Four learning modes and a council where you can gather the figures to discuss or reflect on a topic. Each figure is an AI Echo, an interpretation grounded in primary works, historical context, with a factcheck per figure to show what's verified versus recreated. On privacy: The speech is self hosted on Hetzner GPU servers, Qwen3-TTS for German, Kokoro TTS for English, Faster-Whisper for transcription. 30 free messages per day (EU-hosted for GDPR), BYOK, or you can run it in a full local self-hosted mode.No conversation is stored, no tracking cookies, no profiling, no signup.The app is slow on purpose. Cosmic, no dopamine rush.The mission is to be a doorway, a first step, an introduction to get people interested and outgrow the app to move to primary texts and human teachers.Live at: https://agoracosmica.org

Hacker News3mo agoToolAI

62FL score
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Nucleus – A security-hardened, Nix-native container runtime

Hi HN, I've been building Nucleus, a lightweight Linux container runtime focused on two workloads: ephemeral AI-agent sandboxes and declarative NixOS services. It's a single Rust binary, no daemon.It is not a Docker replacement and not a strict subset of Docker either. I dropped the entire image-and-distribution half (no Dockerfile, no layers, no registry, no pull/push, no persistent storage layer) in exchange for going deeper on isolation and reproducibility. The rootfs is either a directory copied into tmpfs (agent mode) or a Nix-built closure mounted read-only (production mode). If your mental model is "run my image instead of docker run," this won't fit. If it's "run untrusted or ephemeral workloads with stronger, auditable isolation on a single host," that's the target.Things that I think are interesting: - Defense-in-depth defaults. All capabilities dropped, ~100-syscall seccomp allowlist (vs Docker's ~300), up to 8 namespaces including time/cgroup, Landlock LSM path ACLs per service. - Deny-by-default egress. Outbound traffic is denied unless you allow specific CIDRs or DNS-resolved domains. Enforced with namespace-local iptables rules. - Externalized, hash-pinned security policies. seccomp (JSON), capabilities (TOML), and Landlock (TOML) live as separate SHA-256-verified files, decoupled from the rootfs build. There's a nucleus seccomp generate that records syscalls in trace mode and emits a minimal profile. - gVisor as a first-class integrated runtime, not an add-on. Explicit network modes including a gvisor-host mode that's intentionally separate from native host networking. - Nix-native production path. nucleus.lib.mkRootfs builds locked-down closures; rootfs attestation verifies a per-file SHA-256 manifest at startup; first-class NixOS module. - Formal verification. TLA+ specs for the isolation/resource/filesystem/security/gVisor subsystems, checked with

Hacker News3mo agoToolAI

62FL score
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HelixDB – A graph database built on object storage

Hey HN, it’s been just over a year since we launched HelixDB (https://news.ycombinator.com/item?id=43975423), a project a friend and I started in college. It’s an OLTP graph database built on object-storage, with native vector search and full-text search (FTS).Why graph, vector and FTS? Graph databases provide a natural cognitive model for data, vectors allow for a semantic understanding of the entities and relationships in the graph, and FTS provides more specific filtering. Many AI-driven applications attempt to combine all of these functionalities by stitching together multiple disconnected systems, but even then there’s no native way to perform joins or queries that span all systems. You still need to handle this logic at the application level.Helix started as a graph DB, but we moved to a hybrid graph/vector approach after attempting to build an AI memory system, which led us down the GraphRAG and HybridRAG rabbit hole, where we would need separate graph and vector databases.We knew scalability would be a challenge at each stage of our product's development, however our initial focus this past year was to prove out the product through local deployments and was only meant to be run on a single node. Scaling graph DBs remained a difficult and expensive problem we’d have to solve later. Some common ways other graph DBs solve scaling is by duplicating entire datasets across distributed machines (extremely expensive per node), or by sharding the data.Sharding databases is effective and affordable, however, graph data doesn’t have explicit partitions like relational databases do. For example, sharding a relational DB involves splitting up tables. When it comes to graph DBs, the edges can span across any of the partitions, and hopping across multiple machines when traversing nodes is ineffective and computationally expensive.Replicating graph DBs for high availability and better throughput drastically increases the operational cost of the db a

Hacker News3mo agoToolAI

62FL score
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